Selecting Observations against Adversarial Objectives

@inproceedings{Krause2007SelectingOA,
  title={Selecting Observations against Adversarial Objectives},
  author={Andreas Krause and H. Brendan McMahan and Carlos Guestrin and Anupam Gupta},
  booktitle={NIPS},
  year={2007}
}
In many applications, one has to actively select among a set of expensive observations before making an informed decision. Often, we want to select observations which perform well when evaluated with an objective function chosen by an adversary. Examples include minimizing the maximum posterior variance in Gaussian Process regression, robust experimental design, and sensor placement for outbreak detection. In this paper, we present the Submodular Saturation algorithm, a simple and efficient… CONTINUE READING
Highly Cited
This paper has 48 citations. REVIEW CITATIONS